My research interests are in stochastic modelling and Bayesian statistical inference, in particular for infectious disease models. Specific topics include:
(i) Modelling endemic infections. Much work in infection modelling concentrates on the initial emergence of novel pathogens, and the problem of preventing major outbreaks. For diseases which become endemic in a population, other issues come into play; in particular, one is interested in the endemic prevalence level,  and the distribution of the time until fade-out of infection.
(ii) Population heterogeneities. The very simplest mathematical models for infectious spread treat the population as homogeneously mixing. More realistically, many populations can be partitioned into homogeneously-mixing subgroups, eg pens within a pig farm, or management groups within a dairy herd.
(iii) Epidemic control - specifically, applications of mathematical control theory in epidemic modelling.
(iv) Bayesian statistical inference. I have worked on veterinary applications, on theoretical issues in the context of infectious disease models, and on modelling coral reef data.
(v) Veterinary applications, including to E. Coli O157 in dairy cattle, Salmonella in dairy cattle, and Salmonella in pigs.

I obtained my PhD, thesis entitled 'Epidemic Models in Heterogeneous Populations', from the University of Nottingham, under the supervision of Prof Frank Ball. I then held lecturing posts first at the University of Newcastle upon Tyne (Department of Mathematics), then later at the University of Liverpool (Department of Mathematical Sciences). In October 2014 I moved to Heriot-Watt University, where I am a Professor in the Department of Actuarial Mathematics and Statistics. I am a Fellow of the Royal Statistical Society. Much of my research is on the mathematcial structure of stochastic models for infectious disease transmission; I have also worked on several projects of a more applied nature, focusing on livestock infections and zoonoses.